03 Your ecosystem strategy
Ecosystem Architecture & Strategy
What role can you credibly occupy when AI restructures how your industry coordinates?
Your industry's coordination logic is being restructured by AI. The question isn't how to compete inside the existing structure - it's what role you can credibly occupy when the structure itself shifts.
Own the coordination layer - or be coordinated by it.
▍ A quick check
Early signs.
- Value in your industry is fragmenting across more actors, formats, and handoffs than your model was built for.
- AI agents are starting to intermediate transactions you used to own end to end.
- You can't say whether you're a participant in the ecosystem or could become the layer that coordinates it.
- Partnerships keep forming around you rather than through you.
If two or more land, this is likely your question.
▍ The argument underneath
Why this matters.
If you read one section, read this. The argument the engagement is built on, from the ground up.
- 01
Coordination is the scarce resource
When AI drops the cost of producing intelligence to near zero, the binding constraint moves. It is no longer the work itself - it is coordinating the work across the actors, systems, and incentives that have to agree for anything to happen. The firm that resolves that coordination problem captures the position that the firms doing the work no longer can.
- 02
An ecosystem has a coordination logic of its own
Every multi-actor market runs on an implicit logic: how opportunities form, how trust is established, how transactions progress, how outcomes feed back. That logic exists independently of any one firm's org chart. Reconstruct it from first principles and the available strategic roles become visible - including roles no incumbent currently occupies.
- 03
The coordinator captures the durable position
In a restructured ecosystem, durable advantage doesn't sit with the best executor of any single step. It sits with whoever the other actors must route through to coordinate. That position has to be designed and claimed deliberately - it is rarely the one a firm already holds.
▍ The work itself
Our work together.
4 phases. Each builds on the last - from analysis to a blueprint you can act on.
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Reconstruct the coordination logic
Rebuild the ecosystem's coordination logic from the outside in, independent of the client's current structure. Identify the core value drivers and the points where coordination breaks down today.
Deliverable An ecosystem coordination map - value drivers, actors, and the failure points an explicit coordination layer would resolve.
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Model the actors
Model what each actor needs represented - buyer needs, seller capabilities, partner constraints - and the data that drives agentic action: readiness, risk, evidence quality, unresolved dependencies.
Deliverable An actor-representation model spanning every party the coordination layer must serve.
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Design the agentic coordination model
Redesign the ecosystem around an agentic coordination model: how opportunities are formed, how trust is governed, how transactions progress, and how outcomes feed learning back into the intelligence layer.
Deliverable An agentic coordination design covering opportunity formation, trust governance, and the transaction lifecycle.
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Define viable future roles
Translate the analysis into client-specific strategic choices: the viable future roles, the trade-offs between them, and the conditions under which each can be pursued.
Deliverable An agentic ecosystem strategy blueprint with counter-positioned strategic postures and future roles for the firm as a coordination layer.
▍ A recent engagement
Vehicle ownership ecosystem (China)
Joint-venture structuring + ecosystem strategy
Advised the structuring of a joint venture between a leading Chinese tech firm, a global energy major, and a local smart-store OS provider to build an end-to-end ecosystem for the vehicle ownership lifecycle. Despite strong assets in digital scale, supply-chain infrastructure, and retail access, the three partners' aftermarket engagement was fragmented across spare parts, service bookings, and local dealerships - and digital entrants were capturing data and customer relationships through independent platforms, threatening to marginalise all three incumbents. Mapped the coordination failures across the ownership journey, then restructured the ecosystem around a store-centric, AI-driven platform: a unified spare-parts marketplace on the supply side (manufacturers, distributors, workshops), and an AI-powered booking engine on the demand side that predicted service needs and routed traffic to the most reputed nodes. Governance ran on a brand-franchise model anchored in a data reputation system.
▸ The shift
Outcome. China's first AI-driven vehicle maintenance network - a static aftermarket turned into a continuously learning system that optimises pricing, parts availability, store reputation, and customer engagement. Improved asset utilisation, reduced service downtime, and opened up new value-added offerings like warranties and financing - all on a reusable AI coordination layer that aligned the incentives of every ecosystem participant.
Let's discuss further.
If this question is in front of your team, the next step is a short call to scope it. Tell us what you're working through and we'll figure out together whether this is the right place to start.
Let's set up a call▍ Or read first
Further reading.
Short essays from the Reshuffle series that build the argument behind this work.